Deep-learning enabled generalized inverse design of multi-port radio-frequency and sub-terahertz passives and integrated circuits.

ABSTRACT: Millimeter-wave and terahertz integrated circuits and chips are expected to serve as the backbone for future wireless networks and high resolution sensing. However, design of these integrated circuits and chips can be quite complex, requiring years of human expertise, careful tailoring of hand crafted circuit topologies and co-design with parameterized and pre-selected templates of electromagnetic structures. These structures (radiative and non-radiative, single-port and multi-ports) are subsequently optimized through ad-hoc methods and parameter sweeps. Such bottom-up approaches with pre-selected regular topologies also fundamentally limit the design space. Here, we demonstrate a universal inverse design approach for arbitrary-shaped complex multi-port electromagnetic structures with desi

SUBMITTER: Karahan EA 

PROVIDER: S-EPMC11685664 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature